Modern wind energy installations are complex structures which are operated with the aid of a complex control system. The control system is in this case designed to operate as well as possible various wind energy installation systems in accordance with the requirements of the operator of the wind energy installation and the operator of the grid system to which the wind energy installation is connected. In this case, the expression as well as possible generally means that a high energy yield is achieved, although attention must also be paid to the noise emission being as low as possible, to a low load on the drive train, and on the load-bearing structure, and furthermore, to good compatibility with the electrical grid system. The rotor/generator system is particularly important in this context. The rotor together with its blades is of critical importance for the absorption of energy from the wind, that is to say for the conversion of wind energy to mechanical energy, which is in turn converted to electrical energy by the generator. In addition to the design, one important parameter of the rotor relates to the rotor blade length and the profile shape of the rotor blades, the pitch angle which is generally variable. The pitch angle is defined as the angle between a representative profile chord and the rotor plane. The pitch angle is extraordinarily important for definition of the aerodynamic conditions on the rotor blade. It is the governing factor for the flow conditions between the rotor blade and the apparent wind acting on the rotor blade. The apparent wind comprises the true wind and the wind induced by the movement of the rotor blade. The strength and direction of the apparent wind therefore depend on the rotation speed of the rotor, which is in turn dependent on the speed of the true wind and the pitch angle. This therefore results in a closed-loop system for rotor rotation speed control. It is therefore difficult to find optimum values for the pitch angle, as a parameter.
Additionally, values have been used as presets for the rotor blade pitch angle determined in advance during operation of wind energy installations. One disadvantage of this method is that it is highly dependent on the accuracy of the initial calculation. Furthermore, this method is sensitive to discrepancies in the rotor blades from the ideal shape for example resulting from unavoidable manufacturing tolerances. This method therefore does not lead to satisfactory overall results. Furthermore, it is also known from obvious prior use for long-term measurements to be carried out on the wind energy installation, and for appropriate correction values to be derived from them. This avoids the above disadvantages, but this method is time-consuming and costly.
It is also known (DE-A-101 27 451) for parameter variations to be carried out controlled by a timer on a cyclic basis. The method is based on the idea of varying one parameter within predetermined limits until an optimum value is found. One disadvantage of this method is that it is susceptible to finding a local optimum. This conceals the risk of a global optimum not being identified. Furthermore, the method has the disadvantage that it cannot distinguish between stochastic fluctuations in the wind strength and wind direction and real improvements resulting from the changed parameter settings. The method therefore does not always provide satisfactory results.
The invention is based on the object of improving a method of the type mentioned initially such that good optimization is achieved in conditions which are made more difficult by stochastic fluctuations. The solution according to the invention lies in the features of the invention as disclosed broadly herein. Advantageous developments are the subject matter of the specific embodiments disclosed below.
According to the invention, in the case of a method for optimization of operating parameters of a wind energy installation, in particular with respect to its rotor/generator system, a cycle is predetermined with an upper and a lower interval limit value being defined for a parameter to be optimized, in which cycle the wind energy installation is operated alternately with the interval limit values, with one data record in each case being produced with a target variable, to be precise over a variable number of repetitions, evaluation of the data records relating to the interval limit values with a quality measure being formed, identification of the interval limit value with the poorer quality measure, replacement of at least this interval limit value by shifting through a step value Δ in the direction of the other interval limit value, and repetition of the cycle.
The invention is based on the idea of using an iterative process for parameter optimization. The invention has found that an iterative process with a sufficiently large number of samples makes it possible to compensate for stochastic fluctuations so that they virtually no longer have any disturbing effect on the result. In contrast to the known methods, the statistical method according to the invention is not negatively influenced by stochastically fluctuating variables, such as the wind speed and direction. It is therefore very good in practical application, even in difficult conditions.
The concept of the method is of captivating simplicity, and initially requires only two interval limit values for the parameters to be optimized. Building on this, the method is carried out automatically and is able to determine not only an optimum value located between the interval limit values but also an optimum value located outside the interval limit values. The invention achieves this by alternately and successively measuring and storing the desired target parameter relating to the interval limit values. This interaction is repeated a specific number of times. This number can be predetermined as a fixed number or may be variable, depending on the parameter and the optimization quality already achieved, as expressed by the quality measure. Furthermore, the values for the target variable are each evaluated for the two interval limit values, and a quality measure is formed for each of the interval limit values, as a function of the result. The quality measure is a scale for the efficiency with which the wind energy installation is operating for the respective interval limit value. It is determined by comparison in order to establish which of the interval limit values results in the poorer quality measure. The associated interval limit value is the poorer, and the other is the better. The method provides for the poorer interval limit value to be replaced by a different value, which is changed by the variable step value Δ in the direction of the better interval limit value. The procedure is then repeated with the interval using the changed limits. Finally, this results at the end in an optimum value being determined for that parameter. This parameter is preferably the pitch angle of the rotor blades, to be precise for all jointly or individually for each rotor blade. For the method according to the invention, it is preferable for an optimum value for the setting of the rotor blades to be determined automatically. The invention means that there is no longer any need to measure the wind speed in order to calculate an optimum pitch angle. In addition, other parameters which are related to the wind speed and/or to the characteristics of the wind no longer need be measured (or only with less accuracy). The method according to the invention allows optimization without any measurement of wind parameters. In consequence, inaccuracies such as those which generally occur to a considerable extent when measuring the wind parameters (or which can be avoided only by highly complex extra measures), no longer have a negative effect on the operation of the wind energy installation. This is particularly important in the situation where wind energy installations are arranged relatively close in an area such as that which typically occurs in windparks. In this case, adjacent wind energy installations typically have a negative influence on the measurements of wind parameters, such as the wind strength or wind direction. Optimum operation of the wind energy installation is therefore virtually impossible. The invention is based on the surprising discovery that there is no need at all to measure these parameters. Instead of this, the respectively optimum pitch angle is determined by means of the method according to the invention in the respectively prevailing wind conditions, irrespective of the wind direction and strength. A large number of samples or iterations can admittedly lead to lengthening of the time that is required to carry out the method, but this is not of major importance in the case of an automated method, as envisaged by the invention.
The invention results in better utilization of the wind energy installation. This reduces yield reductions resulting from a non-optimum choice of the parameter to be optimized.
A number of expressions used in the following text need to be explained:
A parameter is a system coefficient which influences the system behavior. This may be a parameter of the mechanical system or of the electrical system, or a parameter of the control device.
The target variable to be optimized is a system variable. This results as a consequence of other variables and parameters. Examples of the target variable, are, inter alia, the electrical power output, the noise level emitted, the structural load on the machine resulting from bending and/or vibration loads, as well as variables relating to grid-system compatibility in particular such as flicker. The target variable need not necessarily be a scalar, it can also be composed vectorially from a plurality of variables.
The interval limit values can be predetermined directly at the start of the method. However, it is also possible to calculate the interval limit values, to be precise from an operating value (αB) and a scatter value (αOFF). The latter allows simple inclusion in an existing operating control system. In this case, the parameters as determined in the conventional manner by the operating control system are each used as a start value for the operating value (αB). There is then no need to separately determine a suitable value for starting the method according to the invention.
In general, both of the interval limit values will be changed at the end of a cycle. This is preferably done by changing the operating value. However, it is also possible to envisage a situation in which the aim is to additionally reduce the interval. The change to the better interval limit value is then carried out to a lesser extent, to be precise reduced by a reduction value δ. The interval is thus reduced cyclically and successively until, in the end, the method according to the invention converges at an optimum value. It is also possible to provide for the reduction value to be negative. The range between the interval limit values then widens. This may be advantageous at the start of the optimization process when the aim is to quickly search through quite a wide interval.
The cycle is expediently repeated until a predeterminable termination criterion ε is reached. In this case, ε expediently represents a difference magnitude relating to the quality measure. If this magnitude is sufficiently small, then the optimization process can be ended. However, it is not absolutely essential to use the quality measure for the termination criterion. It is also possible to provide for the cycle to be repeated until the interval limit values have reached a separation of only ε′.
The step width Δ and, if appropriate, the reduction value δ are expediently determined by means of a predictor. This has the advantage over rigid presetting that the predictor frequently makes it possible to achieve faster convergence of the method according to the invention towards an optimum value. Optimization processes which are known per se can be used for the predictor, for example genetic algorithms.
In one proven embodiment, the quality measure is calculated by addition. This is an evaluation and quality-measure formation process which can be calculated particularly easily and efficiently. If the aim is also to take account of the number of data items used, then an averaging process can also be provided. In this case, the expression an average should be understood in the wide sense; the expression covers not only the arithmetic mean but also other calculation methods, such as the geometric mean. It is self-evident that more complex statistical methods can also be provided, in particular those in which the data is weighted over a predeterminable time interval (for example by means of a rectangular or Hamming window).
It is frequently necessary to optimize only one target variable. However, it may also be necessary to optimize a plurality of target variables. In this case, the quality measure is expediently formed multidimensionally. This is preferably done in the form of a vector.
One parameter for the optimization process is preferably the rotor blade pitch angle and the target variable is the electrical power output. As explained initially, the pitch angle of the rotor blades is a significant criterion for the efficiency of absorption of mechanical energy in order to drive the generator from the wind energy. This is therefore a particularly important fact for the electrical power that is generated, and thus for the wind energy installation yield. On the other hand, however, the pitch angle is governed by the flow conditions between the apparent wind and the individual rotor blade, with the apparent wind in turn being governed by the true wind and the rotation speed of the rotor. The rotation speed of the rotor is in turn predominantly governed by the pitch angle. This therefore results in a closed-loop relationship, in which the optimization process according to the invention can be used particularly advantageously.
It is self-evident that the method can also be used for other parameters. By way of example, the generator torque characteristic can be used as a parameter. This likewise has a significant influence on the rotor rotation speed, and thus also on the blade pitch angle. Further expedient parameters are wind parameters, such as windvane offset for determination of inaccuracies or vortices in the area of a windvane of the wind energy installation. It is also possible to optimize other parameters, such as control parameters for control devices for the wind energy installation (for example PID regulators) or parameters for a control system for a converter for the wind energy installation (for example variance of the power, grid-system flicker or harmonics) using the method according to the invention.
It has been proven to use not only one but a plurality of target variables. If, by way of example, one target variable to be optimized is the electrical power output, then it is also possible additionally to use as a target variable a measure of the structural load, for example on the rotor blades, and of the noise emission, and possibly to additionally provide a parameter for the machine load (damage equivalence load).
The invention also relates to a wind energy installation for carrying out the method according to the invention. The wind energy installation has a pod which is arranged on a substructure that has a rotor which is arranged on its end face such that it can rotate, having a generator which is driven by the rotor in order to output electrical energy via a converter, with a control device and a measurement device being provided in order to carry out the method, having a microprocessor and a memory apparatus.